U.S. Artificial Intelligence (AI) Market (By Offering: Hardware, Software, Services, By Technology: Machine Learning, NLP, Context Aware Computing, Computer Vision; By Deployment: On-premise, Cloud-based; By Organization Size: Large Enterprises, SMEs; By Business Function: Marketing, Security, Finance, Others; By End-use) - Regional Outlook and Forecast 2024 to 2033
The U.S. artificial intelligence (AI) market size was valued at USD 37.01 billion in 2023 and is anticipated to reach around USD 369.34 billion by 2033, expanding at a CAGR of 28.83% from 2024 to 2033. The rising demand for artificial intelligence for improving the efficiency and productivity in the businesses that drives teh expansion of the market.
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Artificial intelligence is the recent advancements in technology, it is the computer systems that allows to perform the complex tasks like analysis, reasoning, solving problems, and making decisions. Artificial intelligence is used in a wide range of applications and industries like healthcare, telecommunications, automotive, electronics, and others. Artificial intelligence plays an important role in the business operations to automate the tasks including consumer service work, fraud detection, lead generation and quality control. The artificial intelligence is helps in increasing efficiency and creates the various new opportunities for the growth of the U.S. artificial intelligence market.
Report Coverage | Details |
Growth Rate from 2024 to 2033 | CAGR of 28.83% |
U.S. Artificial Intelligence (AI) Market Size in 2023 | USD 37.01 Billion |
U.S. Artificial Intelligence (AI) Market Size in 2024 | USD 48.51 Billion |
U.S. Artificial Intelligence (AI) Market Size by 2033 | USD 369.34 Billion |
Base Year | 2023 |
Forecast Period | 2024 to 2033 |
Segments Covered | By Offering, By Technology, By Deployment, By Organization Size, By Business Function, and By End-use |
Driver: Artificial intelligence in healthcare
The rising adoption of the artificial intelligence technologies in the healthcare sector in the applications like medical diagnosis, data analysis, drug trials and development, pain management, improving patient outcomes, in pharmaceuticals and others contributing to the growth of the U.S. artificial intelligence market. Artificial intelligence helps in the diagnosis of patients with specific diseases. The number of major pharmaceutical industry is integrating the artificial intelligence for helping in the drug discovery process and reduces the lengthy process of discovering and launching drugs to the market.
Artificial intelligence also helps with the huge amount of data set aiming to help the physician to make informed decisions and manage the patient information effectively. It also helps in the personalized medicine for the better treatment with analyzing the patient data and identifying treatment options. The increasing investment by the U.S. government and major industry leaders on the integration of artificial intelligence, machine learning, and other technologies in the healthcare industry is accelerating the growth of the U.S. artificial intelligence market.
Restraint: Lack of skilled professionals
Shortage of the skilled professionals and the high cost of implementation of AI solutions in the organizations are the major factors that are limiting the expansion of the U.S. artificial intelligence U.S. artificial intelligence market. However, the emergence of Ai-related courses in academics to leverage the significance of AI in multiple industries in the United States is observed to create a solution for the hindering factor.
Opportunity: The investments on the AI research and development
Key players in the United States are focused on increasing federal investment in the artificial intelligence research and development in the collaboration with the academia, industries, international alliances and partners and other non-governmental entities for generating advancement in the artificial intelligence. The United States is investing on the research on the minimizing the challenges for the safer testing, development, deployment, and adaptation of AI technologies. The collaboration of the public and private sector allows strategic leveraging of resources, expertise, and datasets. It also enhances the transformation in research innovations to practices using expertise to published research into the services and products to the marketplace for economic growth.
The software segment dominated the U.S. artificial intelligence market with the share of 39.24% in 2023. Artificial Intelligence as a software is making a wider shift in many sectors as Al systems streamline software development process such as quality testing. Code compilation and reduction of costs and time are a few significant advantages of the same. For example, Al software tools of Google cloud allow developers to work on machine learning design in a cost-effective and time saving manner.
Also, it allows the access of various pre- trained cloud API in order to build machine learning applications such as natural language, computer vision, translation, video, etc. Furthermore, Al as a software enables the execution of complex tasks without any cost outlays. Also, it drives down the time that is used in performing a task. Furthermore, Al software can be operated 24/7 without any interruption or any down time as well as Al software plays with a huge data and reduces human errors, automates the repetitive tasks and processes and facilities quick decision making.
The services segment is expected to show significant growth in the market during the forecast period. Artificial intelligence as a service is employed in large enterprises as well as small enterprises. The employment of artificial intelligence is necessary especially with the amount of advantages Al offers in business management. Additionally, the field of artificial intelligence has experienced ground-breaking advancements in recent times and machine learning techniques have the ability to provide promising results to companies.
As a service, Al can be employed in any branched company especially in current times. Companies that adopt Al and machine learning benefit from a reduction in overall costs as it allows them to cut down the cost on development and research by providing the information by Al, without getting financially involved with the third-party companies.
Further, along with the cost, Al also assists the companies in speeding up the work. Additionally, the Al service provides the company with the required training in how to code and thereby develop complex multi-level infrastructure and hire experts. Also, these services allow the company to customize by corresponding with the data, business and project's needs.
On macro level, the Al services for the organizations are used for:
U.S. Artificial Intelligence Market, by Technology ($Billion)
Technology | 2020 | 2021 | 2022 | 2023 |
Machine Learning | 6.37 | 8.4 | 11.07 | 14.55 |
NLP | 3.64 | 4.81 | 6.35 | 8.36 |
Context Aware Computing | 3.93 | 5.17 | 6.79 | 8.9 |
Computer Vision | 2.31 | 3.03 | 3.97 | 5.19 |
The machine learning segment dominated the U.S. artificial intelligence market with the share of 39.32% CAGR in 2023. Machine learning is an integral part of advanced technologies like artificial intelligence, internet of things (IoT) solutions. Machine learning can be used in the various application on the daily basis such as in the voice assistance in smartphone, email filtering, face unlock features, etc. Machine learning is highly used in the major five industries such as cybersecurity, finance, healthcare, marketing, and retail industry. Machine learning is highly implemented in the retail sector, the rising number of e-commerce industry.
The integration of artificial intelligence, machine learning, and data science that driving the growth of the retail industry. Many of the major e-commerce industries like Amazon, eBay, and others, used machine learning for effective interactions in the functions.
The on-premises segment dominated the U.S. artificial intelligence market with the market share of 50.36% in 2023. Artificial intelligence infrastructure on the on-premises offers various beneficial properties in the organization. On premise AI having the fixed cost model offers potential lower and predictable operational cost over the time.
On premise deployment provides full control over the software and hardware. In the deployment the organization is full control over the security strategies, and implementations with the customizable solutions.
The large enterprises dominated the U.S. artificial intelligence market with the share of 57.13% in 2023. Large enterprises are economically stable in engaging and buying such Al tools that increases their productivity and thereby accounts them profit. For example, Alibaba is a huge e-commerce platform in world, and it uses Al tool called natural language processing that helps in production of product descriptions for websites and additionally helps the firm to acknowledge which products are in demand.
Additionally, the large enterprises adopt Al for improving better user experience and better personalization of the services. Apart from that the use of potential utilizing Al channels assists in automatic identification of the channels that have the best probability of success. Big firms deal with a large amount of complex data, inculcation of Al helps in setting and arranging of the data for easy usage and application.
Furthermore, there are various large enterprises and companies that use Al technology not only in the business but also in their software's. For example, Apple is a global tech company, it used Al in its business strategies along with that they employ Al and machine learning in their devices. For instance, it uses Al in apple music iCloud, facelD and other features. Al has benefited many large enterprises companies including Baidu, Amazon, Google, Facebook, Alibaba and so on.
The others segment led the U.S. artificial intelligence market with the 38.58% in 2023. Advancement in technology is growing vast and artificial intelligence is the main reason behind most of the growing sectors. With the employment of artificial intelligence in marketing, finance, and security, it is also employed majorly in IT operations, and human resources along with research and development. In today's time, every big shot establishment as well as small startups make use of artificial intelligence in IT operations and human resources. By integration of multiple separated manual IT operations tools into an automated set-up that responds easily and proactively assists the company's IT operations to run smoothly.
Basically, it bridges the fine gap between the dynamic and difficult IT landscape to the user's expectations and upcoming trends coupled with advancement in technologies. Human resources on the other hand makes use of Al in other to manage team, time-consuming tasks, and focus on more complex things. Additionally. Al in HR helps to recommend the job to the candidate, predict the performance of the candidate, and find the best candidate.
The advertising and media segment dominated the U.S. artificial intelligence market with the 18.77% market share in 2023. Artificial intelligence helps in analyzing consumer behavior for personalizing and targeted advertising campaigns. AI can allocate budget of the advertisement for both audience and channel, automatically adjust budget to hit KPIs, build richer audience profile, analyzing audience for the audience and opportunities of conversion, determining campaign goals, creates advertisement copy, Hyper-personalize ad targeting, and others. Persadu, Emotiva, Pathmatics, Omneky, Celtra, OneScreen, GumGum, AiAdvertising are the leading tools of the AI advertisement.
The BFSI segment held the second largest share of 17.15% in 2023 in the U.S. artificial intelligence market. The adoption of artificial intelligence in the banking and financial sector increases efficiency in operations and enhances their customer centricity. It has a wide range of applications across middle, front, and back office of the BFSI industry. AI is used in finance, human resources operations, IT operations, application maintenance, and data centers.
Segments Covered in the Report
By Offering
By Technology
By Deployment
By Organization Size
By Business Function
By End-use
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology (Premium Insights)
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on U.S. Artificial Intelligence (AI) Market
5.1. COVID-19 Landscape: U.S. Artificial Intelligence (AI) Industry Impact
5.2. COVID 19 - Impact Assessment for the Industry
5.3. COVID 19 Impact: Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. U.S. Artificial Intelligence (AI) Market, By Offering
8.1. U.S. Artificial Intelligence (AI) Market, by Offering, 2024-2033
8.1.1. Hardware
8.1.1.1. Market Revenue and Forecast (2021-2033)
8.1.2. Software
8.1.2.1. Market Revenue and Forecast (2021-2033)
8.1.3. Services
8.1.3.1. Market Revenue and Forecast (2021-2033)
Chapter 9. U.S. Artificial Intelligence (AI) Market, By Technology
9.1. U.S. Artificial Intelligence (AI) Market, by Technology, 2024-2033
9.1.1. Machine Learning
9.1.1.1. Market Revenue and Forecast (2021-2033)
9.1.2. NLP
9.1.2.1. Market Revenue and Forecast (2021-2033)
9.1.3. Context Aware Computing
9.1.3.1. Market Revenue and Forecast (2021-2033)
9.1.4. Computer Vision
9.1.4.1. Market Revenue and Forecast (2021-2033)
Chapter 10. U.S. Artificial Intelligence (AI) Market, By Deployment
10.1. U.S. Artificial Intelligence (AI) Market, by Deployment, 2024-2033
10.1.1. On-premise
10.1.1.1. Market Revenue and Forecast (2021-2033)
10.1.2. Cloud-based
10.1.2.1. Market Revenue and Forecast (2021-2033)
Chapter 11. U.S. Artificial Intelligence (AI) Market, By Organization Size
11.1. U.S. Artificial Intelligence (AI) Market, by Organization Size, 2024-2033
11.1.1. Large Enterprises
11.1.1.1. Market Revenue and Forecast (2021-2033)
11.1.2. SMEs
11.1.2.1. Market Revenue and Forecast (2021-2033)
Chapter 12. U.S. Artificial Intelligence (AI) Market, By Business Function
12.1. U.S. Artificial Intelligence (AI) Market, by Business Function, 2024-2033
12.1.1. Marketing
12.1.1.1. Market Revenue and Forecast (2021-2033)
12.1.2. Security
12.1.2.1. Market Revenue and Forecast (2021-2033)
12.1.3. Finance
12.1.3.1. Market Revenue and Forecast (2021-2033)
12.1.4. Others
12.1.4.1. Market Revenue and Forecast (2021-2033)
Chapter 13. U.S. Artificial Intelligence (AI) Market, By End-use
13.1. U.S. Artificial Intelligence (AI) Market, by End-use, 2024-2033
13.1.1. Healthcare
13.1.1.1. Market Revenue and Forecast (2021-2033)
13.1.2. BFSI
13.1.2.1. Market Revenue and Forecast (2021-2033)
13.1.3. Law
13.1.3.1. Market Revenue and Forecast (2021-2033)
13.1.4. Retail
13.1.4.1. Market Revenue and Forecast (2021-2033)
13.1.5. Advertising and Media
13.1.5.1. Market Revenue and Forecast (2021-2033)
13.1.6. Automotive and Transportation
13.1.6.1. Market Revenue and Forecast (2021-2033)
13.1.7. Agriculture
13.1.7.1. Market Revenue and Forecast (2021-2033)
13.1.8. Manufacturing
13.1.8.1. Market Revenue and Forecast (2021-2033)
13.1.9. Others
13.1.9.1. Market Revenue and Forecast (2021-2033)
Chapter 14. U.S. Artificial Intelligence (AI) Market, Regional Estimates and Trend Forecast
14.1. U.S.
14.1.1. Market Revenue and Forecast, by Offering (2021-2033)
14.1.2. Market Revenue and Forecast, by Technology (2021-2033)
14.1.3. Market Revenue and Forecast, by Deployment (2021-2033)
14.1.4. Market Revenue and Forecast, by Organization Size (2021-2033)
14.1.5. Market Revenue and Forecast, by Business Function (2021-2033)
14.1.6. Market Revenue and Forecast, by End-use (2021-2033)
Chapter 15. Company Profiles
15.1. AiCure
15.1.1. Company Overview
15.1.2. Product Offerings
15.1.3. Financial Performance
15.1.4. Recent Initiatives
15.2. Atomwise, Inc.
15.2.1. Company Overview
15.2.2. Product Offerings
15.2.3. Financial Performance
15.2.4. Recent Initiatives
15.3. Ayasdi AI LLC
15.3.1. Company Overview
15.3.2. Product Offerings
15.3.3. Financial Performance
15.3.4. Recent Initiatives
15.4. Clarifai, Inc
15.4.1. Company Overview
15.4.2. Product Offerings
15.4.3. Financial Performance
15.4.4. Recent Initiatives
15.5. Cyrcadia Health
15.5.1. Company Overview
15.5.2. Product Offerings
15.5.3. Financial Performance
15.5.4. Recent Initiatives
15.6. Enlitic, Inc.
15.6.1. Company Overview
15.6.2. Product Offerings
15.6.3. Financial Performance
15.6.4. Recent Initiatives
15.7. Google LLC
15.7.1. Company Overview
15.7.2. Product Offerings
15.7.3. Financial Performance
15.7.4. Recent Initiatives
15.8. H2O.ai.
15.8.1. Company Overview
15.8.2. Product Offerings
15.8.3. Financial Performance
15.8.4. Recent Initiatives
15.9. HyperVerge, Inc.
15.9.1. Company Overview
15.9.2. Product Offerings
15.9.3. Financial Performance
15.9.4. Recent Initiatives
15.10. International Business Machines Corporation
15.10.1. Company Overview
15.10.2. Product Offerings
15.10.3. Financial Performance
15.10.4. Recent Initiatives
Chapter 16. Research Methodology
16.1. Primary Research
16.2. Secondary Research
16.3. Assumptions
Chapter 17. Appendix
17.1. About Us
17.2. Glossary of Terms
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